1. Field of the Invention
This invention relates to measurement systems and methods, and more particularly, to systems and methods for obtaining a dimension of an object in an image.
2. Background of the Invention
With technology development and increase on the needs for society security, surveillance systems become a popular research topic and may be used in various applications. Many surveillance systems require a number of video cameras placed in several locations, and the recorded video images may be transmitted through cables or network to storage medium. The recorded video images may be referred to later for further analysis if an accident or incident occurred in the monitored area. Because manual identification is usually relied on for recognition of video images, it is difficult for surveillance systems to provide advance and/or preventive warning. Therefore, development of automatic analysis by computing systems has attracted a lot of attention.
Using visual technique to obtain geometrical information has received wide applications in recent years. Examples of its application include architectural and indoor measurements, reconstruction of objects in paintings, forensic measurements and traffic accident investigation. As an example, the technique may be used to classify people on the scene by their heights as well as for consumer target analysis. One approach to obtaining object dimension is, for example, to place one or more rulers somewhere in the monitored scene so that object dimension may later be estimated with reference to the rulers. Another approach is using a computer to analyze the captured visual information to obtain object dimension offline, sometimes with more accuracy, flexibility and efficiency.
There are a number of computing techniques for measuring objects from an image. For example, Criminisi et al. proposed an approach to compute object measurement from a single perspective images. A. Criminisi and A. Zisserman, Single view metrology, International Conference on Computer Vision, Kekyrn, Greece, September 1999, pp. 434-442. It assumed that the vanishing line of a reference plane in the scene as well as a vanishing point in a reference direction may be determined from the image. Based on the vanishing line and point, distances between any plane which are parallel to the reference plane, area and length ratio on these planes and the camera's position may be computed.
Another approach is to use linear transformation between the camera and the 3D scene to obtain parameters which in turn may be used to compute object dimension. A. Bovyrin and K. Rodyushkin, Human Height Prediction and Roads Estimation for Advanced Video Surveillance Systems, IEEE 2005, pp. 219-223. Wang, et al. proposed to obtain a camera projection matrix first through the homography of a reference space plan and its vertical vanishing point, and then use the matrix and some available scene constraints to retrieve geometrical entities of the scene, such as object height and distance from a point to a line. G. Wang, Z. Hu, F. Wu, and H. Tsui, Single View Metrology From Scene Constraints, Image Vision Computing, Elsevier B.V. 2005. In another approach, object dimension is computed from the parameters obtained through the relationship between two uncalibrated images. Z. Chen, N. Pears, and B. Liang, A Method of Visual Metrology From Uncalibrated Images, Pattern Recognition Letters, Elsevier B.V. 2006.